Transforming Biology From Science To Engineering: Our Investment in Chai Discovery

When you first meet Joshua Meier, it’s impossible not to notice his intense curiosity, clarity of thinking and passion for the problem he’s working on. Within just a few minutes of talking to Josh, I knew this was someone we had to get to know.

Josh has been seeking a better way to do drug discovery since he was a teenager, when he was researching in his high school’s stem cell lab. After graduating from Harvard University, double majoring in CS and Chemistry, Josh joined OpenAI in 2018, where he was exposed to the cutting edge of what AI could do. Despite being one of the most promising young hires there, he left to seek out a place that was truly focused on applying this problem of AI to biology, first at Meta’s FAIR Lab, then at Absci, and ultimately deciding to start Chai Discovery.

Josh and his co-founder, Jack Dent have been friends since their days together in CS125, a notoriously difficult computer science class at Harvard. I’d heard Jack’s name through the Stripe ecosystem, where he became the company’s youngest staff engineer, leading multiple special projects, like Stripe Capital, Stripe Link, and Stripe Billing. Together, their vision and drive are exactly the combination needed to tackle a problem as deeply rooted as the one they’re trying to solve at Chai.

That problem — drug discovery as we know it today — is essentially a brute-force search problem. Bringing a single drug to market can take 10-15 years and $2-3 billion in R&D. The process of finding a drug is a sequence of iterative wet-lab cycles. Early molecular discovery often requires repeated experimental and computational cycles to identify molecules that meet therapeutic properties. The fundamental challenge is that the molecular search space is essentially infinite: there are more possible drug-like molecules than atoms in the observable universe, and biology has given us an incomplete map.

Chai takes a radically new approach, building AI models that predict and reprogram molecular interactions and a software platform that puts those models into the hands of scientists at leading life sciences companies. Instead of relying on large experimental screens of molecular combinations in a lab, scientists can use Chai’s platform to predict how an antibody would bind to a particular target — like designing the perfect key before you ever touch a lock. As the team puts it, the model is the breakthrough, but the product is how it reaches every scientist on earth.

Earlier this year, Chai announced a partnership with Eli Lilly to accelerate the development of its biologics therapeutics, with Lilly deploying Chai’s core models and software platform and Chai building a custom foundation model on Lilly’s data. Just a few weeks ago, Chai announced a second agreement with Pfizer to deploy Chai’s platform for drug discovery. And more recently, they announced a collaboration with Novartis to apply Chai's AI models to antibody discovery across multiple therapeutic programs. When three of the world’s largest pharma companies publicly commit to Chai within months of each other, it tells you how quickly this is moving from promise to practice.

It also speaks to the talent and conviction of the team behind it. At Chai, Josh and Jack are joined by co-founders Matt McPartlon, who leads research, and Jacques Boitreaud, who leads applied science. Together they’ve assembled what they call a RenTec-style guild of mathematicians, physicists, systems hackers, comp-bio PhDs, GPU-kernel wizards, and engineers, describing themselves as a “craft-obsessed team of micro-pessimists and macro-optimists who love what we do.”

Biology is one of the largest and most consequential markets AI has yet to touch. We've been building conviction here for years, with disruptive investments in companies like Cradle and Causaly. Chai is the latest expression of that thesis, and we’re excited to continue to invest in this space.

We’re delighted to partner with Josh, Jack, Matt, Jacques, and the entire Chai team as they continue on their mission to transform biology from science to engineering and build the platform for a new era of drug discovery.